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All Journal Jurnal Informatika Jurnal Inspiration Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Pilar Nusa Mandiri MENENTUKAN PEMILIHAN APLIKASI NONTON FILM SECARA STREAMING PADA SISTEM OPERASI ANDROID MENGGUNAKAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) Jurnal Riset Informatika JISICOM (Journal of Information System, Infomatics and Computing) INTI Nusa Mandiri

Frieyadie Frieyadie

Universitas Nusa Mandiri

Author-ID : 2490434

Computer Science & IT Engineering Other

Published : 11 Documents Claim Missing Document

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IMPLEMENTATION OF INVENTORY INFORMATION SYSTEM DESIGN USING ECONOMIC ORDER QUANTITY METHOD Frieyadie Frieyadie; Tyas Setiyorini
Jurnal Riset Informatika Vol 3 No 2 (2021): Period of March 2021
Publisher : Kresnamedia Publisher

The research problems faced are among others the cost of ordering goods which always changes every time there is an order. Poor product order data collection and less than optimal handling of product orders can harm the company. To solve the problem of controlling inventory management, the Economic Order Quantity (EOQ) method is used, which is proven to be effective in overcoming these problems. Contribution is generated by building an inventory management information system so that the problems faced are not repeated. The purpose of this study is to make the cost of ordering goods more stable and more optimal in handling product orders.

PENINGKATAN KUALITAS CITRA BAWAH AIR BERBASIS ALGORITMA FUSION DENGAN KESEIMBANGAN WARNA, OPTIMALISASI KONTRAS, DAN PEREGANGAN HISTOGRAM Suharyanto Suharyanto; Frieyadie Frieyadie; Sandra Jamu Kuryanti
INTI Nusa Mandiri Vol 16 No 1 (2021): INTI Periode Agustus 2021
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v16i1.2286

Para peneliti saat ini memberikan perhatian yang cukup besar terhadap obyek citra bawah air, kebutuhan akan aplikasi pengamatan citra bawah air memiliki peran yang sangat penting dalam mengidentifikasi objek, pemantauan kehidupan spesies, deteksi kebocoran pipa minyak atau gas, pemantauan polusi, dan sebagainya. Degradasi citra bawah air merupakan fenomena atmosfer yang merupakan hasil dari hamburan dan penyerapan cahaya. Kami menggunakan satu gambar terdistorsi untuk mendapatkan kontras yang ditingkatkan dan versi koreksi warna dari gambar aslinya. Selanjutnya menghilangkan distorsi dan meningkatkan visibilitas objek dalam gambar dengan menerapkan peta bobot, hal ini dapat dicapai dengan menerapkan penyeimbangan warna putih, kemudian penajaman menggunakan gaussian filtering dilakukan untuk, meningkatkan tampilan visual. pada setiap input yang di proses. Langkah terakhir dilakukan menaikan nilai kontras dengan koreksi peregangan kontras yang dibatasi utuk meningkatkan warna keabuan dan uuntuk menhjilangkan efek noise yang berlebihan pada latar belakang obyek gambar. Hasil penelitian evaluasi menggunakan fitur Root Mean Squared Error (RMSE), dan Peak Signal-to-Noise Ratio (PSNR) dan kami bandingkan dengan metode CLAHE. Hasil evaluasi menunjukkan peningkatan PNSR yang signifikan kualitas citra yg di perbaiki menggunakan algoritma kombinasi dibanding dengan menggunakan metode CLAHE sebagaimana yang kami paparkan dalam bagian hasil penelitian.

PENERAPAN KONSEP FINITE STATE AUTOMATA PADA DESAIN VENDING MACHINE ANGKRINGAN Dedik Erwanto; Windu Gata; Laela Kurniawati; Frieyadie Frieyadie; Achmad Bayhaqy
Jurnal Informatika Vol 21, No 2 (2021): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v21i2.3063

Angkringan adalah salah satu kuliner yang berasal dari wilayah Klaten, Surakarta dan Yogyakarta saat ini telah berkembang ke berbagai daerah di Indonesia. Menu khas yang dijual diangkringan adalah nasi kucing dan wedang jahe Lokasi berjualan angkringan biasanya berada di trotoar jalan perkotaan, perkampungan dan tempat wisata dengan menggunakan gerobak tradisional. Pangsa pasar angkringan dapat ditingkatkan dengan menggunakan cara yang lebih modern yaitu dengan vending machine. Desain vending machine angkringan akan menggunakan metode finite state automata untuk memperdalam pengetahuan model komputasi yang paling mendasar. Penelitian ini telah menyajikan penerapan konsep finite state automata pada desain vending machine angkringan yang dapat menghasilkan 15 produk makanan dan minuman khas angkringan dengan pilihan metode pembayaran berupa uang tunai dan uang elektronik. Produk angkringan yang dijual menggunakan vending machine angkringan ini bertujuan untuk meningkatkan pangsa pasar dengan keunggulan berupa otomatisasi, praktis dengan tingkat kebersihan yang lebih baik.

VILLAGE GROUPING BASED ON THE NUMBER OF HEALTH FACILITIES IN WEST JAVA USING K-MEANS CLUSTERING ALGORITHM Frieyadie Frieyadie; Anggie Andriansyah; Tyas Setiyorini
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Health is very important for the welfare and development of the Indonesian nation because as a capital for the implementation of national development, it is essentially the development of all Indonesian people and the development of all Indonesian people. Due to the outbreak of the Covid-19 virus, many health facilities must be provided for patients. Of course, the government must pay attention to the health facilities that can be used in every district/city in West Java in the future. Therefore, to determine the level of availability of sanitation facilities in each district/city in West Java, we need a technology that can classify data correctly. One method of data processing in data mining is clustering. The application of clustering to this problem can use the K-Means algorithm method to group the most frequently used data. The purpose of this study is to classify sanitation data on the highest sanitation facilities, medium sanitation facilities, and low sanitation facilities, so that areas/cities that are included in the low cluster will receive more attention from the government to improve/provide sanitation facilities.

Identifikasi Citra Pap Smear RepoMedUNM dengan Menggunakan K-Means Clustering dan GLCM Dwiza Riana; Sri Rahayu; Sri Hadianti; Frieyadie Frieyadie; Muhamad Hasan; Izni Nur Karimah; Rafly Pratama
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 1 (2022): Februari 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Cervical cancer’s a gynecological malignancy in women that’s very dangerous, even causes death. Prevention through early detection of Pap smear test. It was carried out by pathologists with the help of a microscope still have obstacles in observations. There’re many studies on Pap smear image processing for helping pathologists in cell identification. Availability of Pap smear image dataset is needed in cervical cancer early detection research. The purpose of this study was to segment, feature extraction and classify 180 Pap smear images of RepoMedUNM. The method used to identify Pap smear images begins with preprocessing, namely changing the color in the image to L*a*b color, segmentation using the K-means method, extraction of 6 features, namely metric, eccentricity, contrast, correlation, energy, and homogeneity, and then identified by calculating the closest distance between the training data features and the test data features with the Euclidean distance. The result of identification ThinPrep Pap smear images in 3 classes achieve average accuracy of 93.33%, Non-ThinPrep Pap smear images in 2 classes achieve 90% average accuracy and the average accuracy of the overall in the 4 classes reached 92%. These results indicate that the proposed method can identify Pap smear images well.

APPLICATION OF DECISION TREE AND NAIVE BAYES ON STUDENT PERFORMANCE DATASET Hilda amalia; Ari Puspita; Ade Fitria Lestari; Frieyadie Frieyadie
Jurnal Pilar Nusa Mandiri Vol 18 No 1 (2022): Publishing Period for March 2022
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v18i1.2714

Student performance is the ability of students to deal with the entire academic series taken during school. Student performance produces two labels, namely successful and unsuccessful students. Successful students can graduate with excellent, excellent, and suitable performance labels. At the same time, students who have a label on average are students who get poor performance. Measurement of student performance is needed for every educational institution to take strategic steps to improve student performance. This study aimed to obtain a data mining method that worked well on student performance datasets. In this study, student performance datasets were processed, which had 11 indicators with one result label. Student performance datasets are processed using data mining methods, namely decision tree and nave Bayes, while the tool used for dataset processing is WEKA. The research results from processing student performance datasets obtained that the accuracy value for the decision tree method was 94.3132%, and the accuracy produced by the naive Bayes method was 84.8052%.

READINESS TECHNOLOGY AND SUCCESS MODEL INFORMATION TECHNOLOGY IN IMPLEMENTATION BETWEEN SMEs IN JAKARTA Asrul Sani; Siti Aisyah; Agus Budiyantara; Rouly Doharma; Anton Hindardjo; Frieyadie Frieyadie
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 7 No 2 (2022): JITK Issue February 2022
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v7i2.2981

In general, the use of information technology plays an important role in organizational development. Similarly, if the advancement of information technology can be applied to the financial sector, small and medium enterprises, and so on, the sector's selling value will increase. This study was carried out to determine the level of readiness of the SMEs sector in carrying out information technology implementation projects in business management. In this case, the researcher is developing a research model by combining and adapting a technology readiness model and a success model in the development of information technology to the development of SMEs in Jakarta. This quantitative study included 226 SMEs workers and managers. The data was processed and analyzed using the PLS-SEM method and SmartPLS 3.0 software, with descriptive data being entered into a spreadsheet application. The study also describes the findings of the readiness factor, which has a significant impact on the success of information technology development in Jakarta SMEs

Penerapan Finite State Automata Pada Validasi Permohonan Pengajuan Layanan Akun Digital Menara Masjid Muhammad Romadhona Kusuma; Windu Gata; Laela Kurniawati; Frieyadie Frieyadie; Ahmad Baihaqi
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol 12, No 1 (2022): Jurnal Inspiration Volume 12 Issue 1
Publisher : STMIK AKBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v12i1.2676

DMI Kota Bekasi dalam melaksanakan visi dan misinya yaitu “Optimalisasi peran dan fungsi masjid dalam pemberdayaan umat di era industri 4.0”, memberikan fasilitas berupa penyediaan layanan penggunaan aplikasi digital menara masjid. Pengelolaan pengajuan akun apabila dilakukan secara manual akan menghabiskan waktu yang cukup lama serta kemungkinan terjadi resiko kehilangan data pengajuan. Maksud Penelitian ini dilaksanakan dengan tujuan untuk menghemat waktu, serta memperkecil resiko kehilangan data dan meminimalkan kesalahan pada proses pencatatan permohonan pengajuan akun yang diterima, Pada perancangan sistem ini akan melakukan pengecekan berdasarkan hasil inputan pemohon dan sistem akan secara otomatis melakukan proses validasi, sebelum data tersebut akan disimpan ke dalam basis data menerapkan konsep FSA sehingga data yang akan disimpan sesuai dengan format yang telah ditentukan. Dengan menerapkan hasil penelitian ini, diharapkan dapat membantu DMI Kota Bekasi mengurangi waktu dan memperkecil terjadinya kehilangan data pengajuan, serta meminimalkan terjadinya kesalahan pada proses pencatatan permohonan pengajuan akun karena data pengajuan akan disimpan berdasarkan format yang telah ditentukan.

Performance appraisal employee performance decision-making system in determining salary increases using FSA methods Febri Ainun Jariyah; Windu Gata; , Jordy Lasmana Putra; Frieyadie Frieyadie; Hafifah Bella Novitasari
Journal of Information System, Informatics and Computing Vol 6 No 1 (2022): JISICOM: June 2022
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v6i1.779

Employee performance appraisal is one of the important components of the company in the decision-making process of increasing employee salaries, salaries are wages paid to employees who work for the company, and all employees who work for the company are entitled to receive salaries in accordance with company regulations. The issue of salary acquisition is important because it has a significant impact on work ethic. This research is based on the decision-making process of employee salary increases based on length of service, position, latest education, absenteeism, and work assessment including KK, HK, SK, TJ, KS IK, KD, KP, KJ, KT, DK. The FSA concept can be applied to assist in checking or evaluating performance to determine the percentage increase in employee salary each year. The results of filling out the PA form will result in an increase in employee salary outputs of 0%, 5%, 10%, 15% and 20%. Automata are used to recognize and capture patterns when designing and manufacturing using FSA models.

COMPARISON OF LINEAR REGRESSIONS AND NEURAL NETWORKS FOR FORECASTING COVID-19 RECOVERED CASES Tyas Setiyorini; Frieyadie Frieyadie
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

The emergence of the Covid-19 outbreak for the first time in China killed thousands to millions of people. Since the beginning of the emergence of the number of cases of Covid-19 continues to increase until now. The increase in Covid-19 cases has a very bad impact on health, social and economic life. The need for future forecasting to predict the number of deaths and recoveries from cases that occur, so that the government and the public can understand the spread, prevent and plan actions as early as possible. Several previous studies have forecast the future impact of Covid-19 using the Machine Learning method. Time series forecasting can be done using traditional methods with Linear Regression or Artificial Intelligent methods with neural networks. In this study, it has been proven that there is a linear relationship in the time series data of Covid-19 recovered cases in China, so it is proven that the performance of Linear Regression is better than the Neural Network.

Co-Authors , Jordy Lasmana Putra Achmad Bayhaqy Ade Fitria Lestari Agus Budiyantara Agus Budiyantara Ahmad Baihaqi Anggie Andriansyah Anton Hindardjo Ari Puspita Dedik Erwanto Dwiza Riana Febri Ainun Jariyah Hafifah Bella Novitasari Hilda Amalia Izni Nur Karimah Laela Kurniawati Merliani Ivone Muhamad Hasan Muhammad Romadhona Kusuma Rafly Pratama Rouly Doharma Samuel Samuel Sandra Jamu Kuryanti Sani, Asrul Siti Aisyah Sri Hadianti Sri Rahayu Suharyanto Suharyanto Tyas Setiyorini Tyas Setiyorini Windu Gata

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